DocumentCode
2511978
Title
Salient frame extraction using support vector regression and motion features
Author
Du, Xian ; Dua, Sumeet
Author_Institution
Dept. of Comput. Sci., Louisiana Tech Univ., Ruston, LA, USA
fYear
2010
fDate
14-16 July 2010
Firstpage
122
Lastpage
125
Abstract
We present a new support vector regression (SVR) algorithm to extract salient frames from videos. We use optical flow to describe motion in frames and an adaptive SVR to identify the abrupt change of content in frame sequences. We show that the proposed algorithm is computationally simple and effective in detecting salient frames in video sequences.
Keywords
feature extraction; image motion analysis; image sequences; regression analysis; support vector machines; video signal processing; SVR; frame sequence; motion feature extraction; optical flow; salient frame extraction; support vector regression; video sequence; Adaptive optics; Computer vision; Estimation; Image motion analysis; Optical distortion; Support vector machines; Videos; Salient frame selection; optical flow; support vector regression;
fLanguage
English
Publisher
ieee
Conference_Titel
Aerospace and Electronics Conference (NAECON), Proceedings of the IEEE 2010 National
Conference_Location
Fairborn, OH
ISSN
0547-3578
Print_ISBN
978-1-4244-6576-7
Type
conf
DOI
10.1109/NAECON.2010.5712934
Filename
5712934
Link To Document